Multiple antibodies targeting tumor-specific mutations redirect immune cells to inhibit tumor growth and increase survival in experimental animal models

G. S. Shukla, S. C. Pero, Y. J. Sun, L. Mei, F. Zhang, G. Sholler, D. N. Krag

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Background: T cell therapy for cancer involves genetic introduction of a target-binding feature into autologous T cells, ex vivo expansion and single large bolus administration back to the patient. These reprogrammed T cells can be highly effective in killing cells, but tumor heterogeneity results in regrowth of cells that do not sufficiently express the single antigen being targeted. We describe a cell-based therapy that simultaneously targets multiple tumor-specific antigens. Methods: High-affinity polyclonal rabbit antibodies were generated against nine different surface-related tumor-specific mutations on B16F10 cells. Unsorted splenic effector cells from syngeneic mice were incubated with a cocktail of the nine anti-B16F10 antibodies. These ‘armed’ effector cells were used to treat mice previously inoculated with B16F10 melanoma cells. Results: The cocktail of nine antibodies resulted in dense homogeneous binding to histological sections of B16F10 cells. Five treatments with the armed effector cells and PD1 inhibition inhibited tumor growth and improved survival. Shortening the interval of the five treatments from every three days to every day increased survival. Arming effector cells with the four antibodies showing best binding to B16F10 cells even further increased survival. Conclusions: This study demonstrates that ex vivo arming a mixed population of immune effector cells with antibodies targeting multiple tumor-specific mutated proteins in conjunction with PD1 inhibition delayed tumor growth and prolonged survival in mice inoculated with an aggressive melanoma. A remarkably low total antibody dose of less than 5 µg was sufficient to accomplish tumor inhibition. Scaling up to clinical level may be feasible.

Original languageEnglish (US)
Pages (from-to)1094-1104
Number of pages11
JournalClinical and Translational Oncology
Volume22
Issue number7
DOIs
StatePublished - Jul 1 2020

All Science Journal Classification (ASJC) codes

  • Oncology
  • Cancer Research

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